Accelerating climate change and ecosystem degradation demand advanced vegetation monitoring to support global sustainability goals, yet conventional remote sensing faces critical limitations: fragmented data sources, sparse 3D structural insights, and prohibitive costs for high-resolution surveys. New AI-integrated methodologies address these gaps—exemplified by Google’s AlphaEarth unifying multi-source data into 10m-grid planetary embeddings, China’s L-band interferometry enabling single-baseline forest 3D mapping, among others. These innovations directly serve urgent applications, with vegetation underpinning 30% of climate mitigation pathways (IPCC AR6).

Despite major advances, accurate and scalable vegetation assessment remains constrained by fragmented data streams, spectral–spatial trade-offs, persistent cloud contamination, and limited vertical-structure sampling. Therefore, establishing a scalable, AI-driven framework that fuses satellite, UAV, and ground observations is crucial to accelerating ecological governance, strengthening agricultural resilience, and advancing global carbon-neutrality initiatives.

This Research Topic welcomes original research articles, reviews, and meta-analyses published by Frontiers in Plant Science that advance the understanding of vegetation-climate interactions, with particular emphasis on:

• Merging multi-source remote sensing images, geographical big data, and artificial intelligence methods to achieve refined extraction or change detection of vegetation information

• Combining artificial intelligence and remote sensing technology, identify diseases and pests in forests, grasslands, and crops

• Integrating remote sensing and ecological models to quantitatively assess the carbon sequestration capacity of various ecosystems and to analyze their spatiotemporal dynamics

• Responses of vegetation structure and physiological function to climate change, focusing on changes in greenness and physiological traits and their underlying mechanisms

Are you interested in contributing a manuscript to this Research Topic?

New Methods and Applications of Vegetation Remote Sensing Monitoring